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Mathematical Problems in Engineering
Volume 2013 (2013), Article ID 725017, 13 pages
http://dx.doi.org/10.1155/2013/725017
Research Article

Identification of Fuzzy Inference Systems by Means of a Multiobjective Opposition-Based Space Search Algorithm

1State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing 100191, China
2School of Computer and Communication Engineering, Tianjin University of Technology, Tianjin 300384, China
3Department of Electrical Engineering, The University of Suwon, San 2-2, Wau-ri, Bongdam-eup, Gyeonggi-do, Hwaseong-si 445-743, Republic of Korea

Received 2 January 2013; Revised 25 February 2013; Accepted 25 February 2013

Academic Editor: Zhuming Bi

Copyright © 2013 Wei Huang and Sung-Kwun Oh. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

We introduce a new category of fuzzy inference systems with the aid of a multiobjective opposition-based space search algorithm (MOSSA). The proposed MOSSA is essentially a multiobjective space search algorithm improved by using an opposition-based learning that employs a so-called opposite numbers mechanism to speed up the convergence of the optimization algorithm. In the identification of fuzzy inference system, the MOSSA is exploited to carry out the parametric identification of the fuzzy model as well as to realize its structural identification. Experimental results demonstrate the effectiveness of the proposed fuzzy models.